casper paper ethereum

protocol overlaid onto Ethereum's Proof-of-Work blockchain. We ticularly relevant for this paper as it is used for the Casper. contract. Casper Basics Here we discuss this paper: Economics Block proposer This is for discussing the implementation of the full proof of stake system. E.g., going. Topics discussed in the episode · Ethereum Foundation · Ethereum R&D Roundup Valentine's Day · December Development Roundup · R3 Chain Interoperability Paper. LONG TERM FOREX ANALYSIS TODAY

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Most probably, yes, although this is due to the economics of Casper rather than due to its blockchain architecture. Validators will likely be earning only transaction fees, so they have a direct incentive to increase the gas limit, if their validation server can handle the load. However, validators also have reduced returns from causing other, slower validators to fall out of sync, so they will allow the gas limit to rise only in a manner that is tolerable by the other validators.

Miners investing in hardware primarily purchase more mining rigs, while validators investing in hardware primarily upgrade their servers so they can process more transactions per second. Miners also have an incentive to reinvest in more powerful transaction processing, but this incentive is much weaker than their incentive to purchase mining power.

Security-deposit-based proof-of-stake is very light-client friendly relative to proof-of-work. Specifically, light clients do not need to download block headers to have full security in authenticating the consensus, or to have full economic assurances of valid transaction execution.

This means that a lot of consensus overhead affects only the validators, but not the light clients, and it allows for lower latency without causing light clients to lose the ability to authenticate the consensus. Recovery from netsplits Casper is able to recover from network partitions because transactions in non-finalized blocks can be reverted. After a partition reconnects, Casper executes transactions from blocks that received bets on the partition with higher validator participation.

In this manner, nodes from either side of the partition agree on the state of the consensus after a reconnection and before validators are able to replace their bets. Validator bets converge to finalize the blocks in the partition that had more validator participation, with very high probability. Casper will very likely process the losing transactions from losing blocks after the ones from winning blocks, although it is still to be decided whether validators will have to include these transactions in new blocks, or if Casper will execute them in their original order, himself.

Recovery from mass crash-failure Casper is able to recover from the crash-failure of all but one node. Bonded validators can always produce and place bets on blocks on their own, although they always make higher returns by coordinating on the production of blocks with a larger set of validators. In any case, a validator makes higher returns from producing blocks than from not producing blocks at all. Additionally, bonded validators who appear to be offline for too long will be unbonded, and new bonders subsequently will be allowed to join the validation set.

Casper can thereby potentially recover precisely the security guarantees it had before the mass crash-failure. What is Casper, in non-economic terms? Casper is an eventually-consistent blockchain-based consensus protocol. It favours availability over consistency see the CAP theorem. It is always available, and consistent whenever possible.

It is robust to unpredictable message delivery times because nodes come to consensus via re-organization of transactions, after delayed messages are eventually received. Clients therefore only consider a block as finalized if it has the participation of a supermajority of validators or bonded stake. What is it like to be a bonded validator? As a bonded validator, you will need to securely sign blocks and place bets on the consensus process. If you have a very large deposit, you will probably have a handful of servers in a custom multisig arrangement for validation, to minimize the chance of your server misbehaving or being hacked.

This will require experimentation and technical expertise. The validator should be kept online as reliably and as much as possible, for it to maximize its profitability or for otherwise it will be unprofitable. It will be very advisable to buy DDoS protection. Additionally, your profitability will depend on the performance and availability of the other bonded validators.

This means that there is risk that you cannot directly mitigate, yourself. However, additional risk also often means higher average profitability - especially if the risk is perceived but the costly event never occurs. What is it like to be an application or a user? Applications and their users benefit a lot from the change from proof-of-work consensus to Casper. In normal conditions transactions finalize very quickly.

Ethereum Casper is an evolutionary tale of transformation in the blockchain network. So, you may also hear it referred to as Ethereum 2. Casper Ethereum 2. A short history Ethereum has only been around since The reason for this is its blockchain design allows for easy deployment of decentralized applications dApps.

In the pipeline are two co-developed Casper implementations helping transform the Ethereum ecosystem. Both of which began a few years ago. However, Casper CBC, which was founded by Vlad Zamfir, has since made what is widely considered to be a superior protocol. Meanwhile, CBC is being used elsewhere because Casper is not exclusive to Ethereum but can be used on other blockchains.

PoW and PoS are consensus protocols. They determine how the chain adds blocks to the network. PoW is the protocol currently used by Ethereum and the primary reasons to switch to PoS is security, speed and scalability. However, there are opponents on both sides of the fence and the battle has been raging for over three years.

In Proof of Work, miners get rewarded for mining. For instance, Bitcoin uses a PoW protocol. Why the ghostly name? In PoW mining, blocks are added to a chain when the miner solves a computational puzzle against other miners. In blockchain mining, sometimes blocks are mined and then abandoned with preference for a longer chain. If this is allowed to continue unchecked, it could potentially lead to centralization of the network.

As Ethereum is a decentralized network, that poses a problem. Therefore, Ethereum opts to reward the creation of these abandoned blocks so that more nodes can retain power than simply the biggest, longest chain. And from here we get the preference for PoS. So, yes, the name Casper really does derive from the friendly animated ghost. These will be selected based on the stake the block validator holds.

These block validators will replace the miners. For example, tricking the system, double spending, reversing history.

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Therefore, when clients receive and authenticate the state of the consensus, their authentication chain ends in the list of currently-bonded validators. In proof-of-work consensus, on the other hand, the authentication chain ends in the genesis block - as long as you know the genesis block you can authenticate the consensus. Here, as long as you know the set of currently-bonded validators, you can authenticate the consensus.

A client who does not know the list of currently bonded validators must authenticate this list out-of-band. The validator list changes over time as validators place deposits, lose their deposits, unbond, and get unbonded. Therefore, if clients are offline for too long, their validator list will no longer be current enough to authenticate the consensus. In the case that they are online sufficiently often to observe the validator set rotating, however, clients are able to securely update their validator list.

Even in this case, clients must begin with an up-to-date list of currently-bonded validators, and therefore they must authenticate this list out-of-band at least once. In weakly subjective consensus protocols, the fork-choice rule is stateful, and clients must initialize and possibly sometimes renew the information that their fork-choice rule uses to authenticate the consensus. In our case, this entails identifying the currently bonded validators or, more probably a cryptographic hash of the validator list.

Gambling on Consensus Casper makes validators bet a large part of their security deposits on how the consensus process will turn out. If they bet correctly, they earn their deposit back with transaction fees and possibly token issuance upon it — if on the other hand they do not quickly agree, they re-earn less of their deposit. Therefore through iterated rounds of betting validator bets converge.

Moreover, if validators change their bets too dramatically, for example by voting with a high probability on one block after voting with a very high probability on another, then they are severely punished.

This guarantees that validators bet with very high probabilities only when they are confident that the other validators will also produce high probability bets. Through this mechanism we guarantee that their bets never converge to a second value after converging upon a first, as long as there there is sufficient validator participation. Proof-of-work consensus is also a betting scheme: miners bet that their block will be part of the heaviest chain; if they eventually prove to be correct, they receive tokens - whereas if they prove to be incorrect, they incur electricity costs without compensation.

Consensus is secured as long as all miners are betting their hashing power on the same chain, making it the blockchain with the most work as a direct result of and as preempted by their coordinated betting. The economic cost of these proof-of-work bets add up linearly in the number of confirmations generations of descendant blocks , while, in Casper, validators can coordinate placing exponentially growing portions of their security deposits against blocks, thereby achieving maximum security very quickly.

By-height Consensus Validators bet independently on blocks at every height i. Through iterative betting, the validators elect exactly one block at every height, and this process determines the order in which transactions are executed.

Additionally, when a client sees that every block lower than some height H is final, then the client will never choose a fork that has a different application state at height H - 1 than the one that results from the execution of transactions in these finalized blocks. In this eventuality, we say that this state is finalized.

Censorship Resistance One of the largest risks to consensus protocols is the formation of coalitions that aim to maximize the profits of their members at the expense of non-members. Additionally, an attacker could bribe nodes to exclude transactions affecting particular addresses — and so long as a majority of nodes are rational, they can censor the blocks created by nodes who include these transactions. More specifically, Casper punishes validators for not creating blocks in a protocol-prescribed order.

The protocol is aware of deviations from this order, and withholds transaction fees and deposits from validators accordingly. Additionally, the revenue made from betting correctly on blocks is linear or superlinear in the number of validators who are participating in at that height of the consensus game.

Will there be more transactions per second? Most probably, yes, although this is due to the economics of Casper rather than due to its blockchain architecture. Validators will likely be earning only transaction fees, so they have a direct incentive to increase the gas limit, if their validation server can handle the load.

However, validators also have reduced returns from causing other, slower validators to fall out of sync, so they will allow the gas limit to rise only in a manner that is tolerable by the other validators. Miners investing in hardware primarily purchase more mining rigs, while validators investing in hardware primarily upgrade their servers so they can process more transactions per second. Miners also have an incentive to reinvest in more powerful transaction processing, but this incentive is much weaker than their incentive to purchase mining power.

Security-deposit-based proof-of-stake is very light-client friendly relative to proof-of-work. Specifically, light clients do not need to download block headers to have full security in authenticating the consensus, or to have full economic assurances of valid transaction execution.

Messages Contracts have the ability to send "messages" to other contracts. Messages are virtual objects that are never serialized and exist only in the Ethereum execution environment. A message contains: The sender of the message implicit The recipient of the message The amount of ether to transfer alongside the message An optional data field A STARTGAS value Essentially, a message is like a transaction, except it is produced by a contract and not an external actor.

A message is produced when a contract currently executing code executes the CALL opcode, which produces and executes a message. Like a transaction, a message leads to the recipient account running its code. Thus, contracts can have relationships with other contracts in exactly the same way that external actors can.

Note that the gas allowance assigned by a transaction or contract applies to the total gas consumed by that transaction and all sub-executions. For example, if an external actor A sends a transaction to B with gas, and B consumes gas before sending a message to C, and the internal execution of C consumes gas before returning, then B can spend another gas before running out of gas. If not, return an error.

Subtract the fee from the sender's account balance and increment the sender's nonce. If there is not enough balance to spend, return an error. Transfer the transaction value from the sender's account to the receiving account. If the receiving account does not yet exist, create it. If the receiving account is a contract, run the contract's code either to completion or until the execution runs out of gas. If the value transfer failed because the sender did not have enough money, or the code execution ran out of gas, revert all state changes except the payment of the fees, and add the fees to the miner's account.

Otherwise, refund the fees for all remaining gas to the sender, and send the fees paid for gas consumed to the miner. For example, suppose that the contract's code is: if! Suppose that the contract's storage starts off empty, and a transaction is sent with 10 ether value, gas, 0. The process for the state transition function in this case is as follows: Check that the transaction is valid and well formed.

If it is, then subtract 2 ether from the sender's account. Subtract 10 more ether from the sender's account, and add it to the contract's account. Run the code. In this case, this is simple: it checks if the contract's storage at index 2 is used, notices that it is not, and so it sets the storage at index 2 to the value CHARLIE. If there was no contract at the receiving end of the transaction, then the total transaction fee would simply be equal to the provided GASPRICE multiplied by the length of the transaction in bytes, and the data sent alongside the transaction would be irrelevant.

Note that messages work equivalently to transactions in terms of reverts: if a message execution runs out of gas, then that message's execution, and all other executions triggered by that execution, revert, but parent executions do not need to revert.

This means that it is "safe" for a contract to call another contract, as if A calls B with G gas then A's execution is guaranteed to lose at most G gas. Finally, note that there is an opcode, CREATE, that creates a contract; its execution mechanics are generally similar to CALL, with the exception that the output of the execution determines the code of a newly created contract.

Code Execution The code in Ethereum contracts is written in a low-level, stack-based bytecode language, referred to as "Ethereum virtual machine code" or "EVM code". The code consists of a series of bytes, where each byte represents an operation. In general, code execution is an infinite loop that consists of repeatedly carrying out the operation at the current program counter which begins at zero and then incrementing the program counter by one, until the end of the code is reached or an error or STOP or RETURN instruction is detected.

Unlike stack and memory, which reset after computation ends, storage persists for the long term. The code can also access the value, sender and data of the incoming message, as well as block header data, and the code can also return a byte array of data as an output.

The formal execution model of EVM code is surprisingly simple. For example, ADD pops two items off the stack and pushes their sum, reduces gas by 1 and increments pc by 1, and SSTORE pushes the top two items off the stack and inserts the second item into the contract's storage at the index specified by the first item. Although there are many ways to optimize Ethereum virtual machine execution via just-in-time compilation, a basic implementation of Ethereum can be done in a few hundred lines of code.

Blockchain and Mining The Ethereum blockchain is in many ways similar to the Bitcoin blockchain, although it does have some differences. The main difference between Ethereum and Bitcoin with regard to the blockchain architecture is that, unlike Bitcoin, Ethereum blocks contain a copy of both the transaction list and the most recent state. Aside from that, two other values, the block number and the difficulty, are also stored in the block.

The basic block validation algorithm in Ethereum is as follows: Check if the previous block referenced exists and is valid. Check that the timestamp of the block is greater than that of the referenced previous block and less than 15 minutes into the future Check that the block number, difficulty, transaction root, uncle root and gas limit various low-level Ethereum-specific concepts are valid. Check that the proof-of-work on the block is valid.

Let TX be the block's transaction list, with n transactions. If it is, the block is valid; otherwise, it is not valid. The approach may seem highly inefficient at first glance, because it needs to store the entire state with each block, but in reality efficiency should be comparable to that of Bitcoin. The reason is that the state is stored in the tree structure, and after every block only a small part of the tree needs to be changed. Thus, in general, between two adjacent blocks the vast majority of the tree should be the same, and therefore the data can be stored once and referenced twice using pointers ie.

A special kind of tree known as a "Patricia tree" is used to accomplish this, including a modification to the Merkle tree concept that allows for nodes to be inserted and deleted, and not just changed, efficiently. Additionally, because all of the state information is part of the last block, there is no need to store the entire blockchain history - a strategy which, if it could be applied to Bitcoin, can be calculated to provide x savings in space.

A commonly asked question is "where" contract code is executed, in terms of physical hardware. This has a simple answer: the process of executing contract code is part of the definition of the state transition function, which is part of the block validation algorithm, so if a transaction is added into block B the code execution spawned by that transaction will be executed by all nodes, now and in the future, that download and validate block B.

Applications In general, there are three types of applications on top of Ethereum. The first category is financial applications, providing users with more powerful ways of managing and entering into contracts using their money. This includes sub-currencies, financial derivatives, hedging contracts, savings wallets, wills, and ultimately even some classes of full-scale employment contracts. The second category is semi-financial applications, where money is involved but there is also a heavy non-monetary side to what is being done; a perfect example is self-enforcing bounties for solutions to computational problems.

Finally, there are applications such as online voting and decentralized governance that are not financial at all. Token Systems On-blockchain token systems have many applications ranging from sub-currencies representing assets such as USD or gold to company stocks, individual tokens representing smart property, secure unforgeable coupons, and even token systems with no ties to conventional value at all, used as point systems for incentivization.

Token systems are surprisingly easy to implement in Ethereum. The key point to understand is that all a currency, or token system, fundamentally is, is a database with one operation: subtract X units from A and give X units to B, with the proviso that i A had at least X units before the transaction and 2 the transaction is approved by A.

All that it takes to implement a token system is to implement this logic into a contract. The basic code for implementing a token system in Serpent looks as follows: def send to, value : if self. A few extra lines of code need to be added to provide for the initial step of distributing the currency units in the first place and a few other edge cases, and ideally a function would be added to let other contracts query for the balance of an address.

But that's all there is to it. Theoretically, Ethereum-based token systems acting as sub-currencies can potentially include another important feature that on-chain Bitcoin-based meta-currencies lack: the ability to pay transaction fees directly in that currency.

The way this would be implemented is that the contract would maintain an ether balance with which it would refund ether used to pay fees to the sender, and it would refill this balance by collecting the internal currency units that it takes in fees and reselling them in a constant running auction. Users would thus need to "activate" their accounts with ether, but once the ether is there it would be reusable because the contract would refund it each time.

Financial derivatives and Stable-Value Currencies Financial derivatives are the most common application of a "smart contract", and one of the simplest to implement in code. The simplest way to do this is through a "data feed" contract maintained by a specific party eg. NASDAQ designed so that that party has the ability to update the contract as needed, and providing an interface that allows other contracts to send a message to that contract and get back a response that provides the price.

Given that critical ingredient, the hedging contract would look as follows: Wait for party A to input ether. Wait for party B to input ether. Such a contract would have significant potential in crypto-commerce. Up until now, the most commonly proposed solution has been issuer-backed assets; the idea is that an issuer creates a sub-currency in which they have the right to issue and revoke units, and provide one unit of the currency to anyone who provides them offline with one unit of a specified underlying asset eg.

The issuer then promises to provide one unit of the underlying asset to anyone who sends back one unit of the crypto-asset. This mechanism allows any non-cryptographic asset to be "uplifted" into a cryptographic asset, provided that the issuer can be trusted.

In practice, however, issuers are not always trustworthy, and in some cases the banking infrastructure is too weak, or too hostile, for such services to exist. Financial derivatives provide an alternative. Here, instead of a single issuer providing the funds to back up an asset, a decentralized market of speculators, betting that the price of a cryptographic reference asset eg.

ETH will go up, plays that role. Unlike issuers, speculators have no option to default on their side of the bargain because the hedging contract holds their funds in escrow. Note that this approach is not fully decentralized, because a trusted source is still needed to provide the price ticker, although arguably even still this is a massive improvement in terms of reducing infrastructure requirements unlike being an issuer, issuing a price feed requires no licenses and can likely be categorized as free speech and reducing the potential for fraud.

Identity and Reputation Systems The earliest alternative cryptocurrency of all, Namecoin , attempted to use a Bitcoin-like blockchain to provide a name registration system, where users can register their names in a public database alongside other data.

The major cited use case is for a DNS system, mapping domain names like "bitcoin. Other use cases include email authentication and potentially more advanced reputation systems. Here is the basic contract to provide a Namecoin-like name registration system on Ethereum: def register name, value : if!

Anyone can register a name with some value, and that registration then sticks forever. A more sophisticated name registration contract will also have a "function clause" allowing other contracts to query it, as well as a mechanism for the "owner" ie.

One can even add reputation and web-of-trust functionality on top. Decentralized File Storage Over the past few years, there have emerged a number of popular online file storage startups, the most prominent being Dropbox, seeking to allow users to upload a backup of their hard drive and have the service store the backup and allow the user to access it in exchange for a monthly fee. However, at this point the file storage market is at times relatively inefficient; a cursory look at various existing solutions shows that, particularly at the "uncanny valley" GB level at which neither free quotas nor enterprise-level discounts kick in, monthly prices for mainstream file storage costs are such that you are paying for more than the cost of the entire hard drive in a single month.

Ethereum contracts can allow for the development of a decentralized file storage ecosystem, where individual users can earn small quantities of money by renting out their own hard drives and unused space can be used to further drive down the costs of file storage.

The key underpinning piece of such a device would be what we have termed the "decentralized Dropbox contract". This contract works as follows. First, one splits the desired data up into blocks, encrypting each block for privacy, and builds a Merkle tree out of it. One then makes a contract with the rule that, every N blocks, the contract would pick a random index in the Merkle tree using the previous block hash, accessible from contract code, as a source of randomness , and give X ether to the first entity to supply a transaction with a simplified payment verification-like proof of ownership of the block at that particular index in the tree.

When a user wants to re-download their file, they can use a micropayment channel protocol eg. An important feature of the protocol is that, although it may seem like one is trusting many random nodes not to decide to forget the file, one can reduce that risk down to near-zero by splitting the file into many pieces via secret sharing, and watching the contracts to see each piece is still in some node's possession.

If a contract is still paying out money, that provides a cryptographic proof that someone out there is still storing the file. The members would collectively decide on how the organization should allocate its funds.

Methods for allocating a DAO's funds could range from bounties, salaries to even more exotic mechanisms such as an internal currency to reward work. This essentially replicates the legal trappings of a traditional company or nonprofit but using only cryptographic blockchain technology for enforcement.

The requirement that one person can only have one membership would then need to be enforced collectively by the group. A general outline for how to code a DAO is as follows. The simplest design is simply a piece of self-modifying code that changes if two thirds of members agree on a change. Although code is theoretically immutable, one can easily get around this and have de-facto mutability by having chunks of the code in separate contracts, and having the address of which contracts to call stored in the modifiable storage.

In a simple implementation of such a DAO contract, there would be three transaction types, distinguished by the data provided in the transaction: [0,i,K,V] to register a proposal with index i to change the address at storage index K to value V [1,i] to register a vote in favor of proposal i [2,i] to finalize proposal i if enough votes have been made The contract would then have clauses for each of these.

It would maintain a record of all open storage changes, along with a list of who voted for them. It would also have a list of all members. When any storage change gets to two thirds of members voting for it, a finalizing transaction could execute the change. A more sophisticated skeleton would also have built-in voting ability for features like sending a transaction, adding members and removing members, and may even provide for Liquid Democracy -style vote delegation ie.

This design would allow the DAO to grow organically as a decentralized community, allowing people to eventually delegate the task of filtering out who is a member to specialists, although unlike in the "current system" specialists can easily pop in and out of existence over time as individual community members change their alignments. An alternative model is for a decentralized corporation, where any account can have zero or more shares, and two thirds of the shares are required to make a decision.

A complete skeleton would involve asset management functionality, the ability to make an offer to buy or sell shares, and the ability to accept offers preferably with an order-matching mechanism inside the contract. Delegation would also exist Liquid Democracy-style, generalizing the concept of a "board of directors".

Further Applications 1. Savings wallets. Suppose that Alice wants to keep her funds safe, but is worried that she will lose or someone will hack her private key. Alice and Bob together can withdraw anything. If Alice's key gets hacked, she runs to Bob to move the funds to a new contract.

If she loses her key, Bob will get the funds out eventually. If Bob turns out to be malicious, then she can turn off his ability to withdraw. Crop insurance. One can easily make a financial derivatives contract but using a data feed of the weather instead of any price index. If a farmer in Iowa purchases a derivative that pays out inversely based on the precipitation in Iowa, then if there is a drought, the farmer will automatically receive money and if there is enough rain the farmer will be happy because their crops would do well.

This can be expanded to natural disaster insurance generally. A decentralized data feed. For financial contracts for difference, it may actually be possible to decentralize the data feed via a protocol called " SchellingCoin ". SchellingCoin basically works as follows: N parties all put into the system the value of a given datum eg. Everyone has the incentive to provide the answer that everyone else will provide, and the only value that a large number of players can realistically agree on is the obvious default: the truth.

Smart multisignature escrow. Bitcoin allows multisignature transaction contracts where, for example, three out of a given five keys can spend the funds. Additionally, Ethereum multisig is asynchronous - two parties can register their signatures on the blockchain at different times and the last signature will automatically send the transaction.

Cloud computing. The EVM technology can also be used to create a verifiable computing environment, allowing users to ask others to carry out computations and then optionally ask for proofs that computations at certain randomly selected checkpoints were done correctly. This allows for the creation of a cloud computing market where any user can participate with their desktop, laptop or specialized server, and spot-checking together with security deposits can be used to ensure that the system is trustworthy ie.

Although such a system may not be suitable for all tasks; tasks that require a high level of inter-process communication, for example, cannot easily be done on a large cloud of nodes. Other tasks, however, are much easier to parallelize; projects like SETI home, folding home and genetic algorithms can easily be implemented on top of such a platform. Peer-to-peer gambling. Any number of peer-to-peer gambling protocols, such as Frank Stajano and Richard Clayton's Cyberdice , can be implemented on the Ethereum blockchain.

The simplest gambling protocol is actually simply a contract for difference on the next block hash, and more advanced protocols can be built up from there, creating gambling services with near-zero fees that have no ability to cheat. Prediction markets. Provided an oracle or SchellingCoin, prediction markets are also easy to implement, and prediction markets together with SchellingCoin may prove to be the first mainstream application of futarchy as a governance protocol for decentralized organizations.

On-chain decentralized marketplaces, using the identity and reputation system as a base. The motivation behind GHOST is that blockchains with fast confirmation times currently suffer from reduced security due to a high stale rate - because blocks take a certain time to propagate through the network, if miner A mines a block and then miner B happens to mine another block before miner A's block propagates to B, miner B's block will end up wasted and will not contribute to network security.

Thus, if the block interval is short enough for the stale rate to be high, A will be substantially more efficient simply by virtue of its size. With these two effects combined, blockchains which produce blocks quickly are very likely to lead to one mining pool having a large enough percentage of the network hashpower to have de facto control over the mining process.

As described by Sompolinsky and Zohar, GHOST solves the first issue of network security loss by including stale blocks in the calculation of which chain is the "longest"; that is to say, not just the parent and further ancestors of a block, but also the stale descendants of the block's ancestor in Ethereum jargon, "uncles" are added to the calculation of which block has the largest total proof-of-work backing it. To solve the second issue of centralization bias, we go beyond the protocol described by Sompolinsky and Zohar, and also provide block rewards to stales: a stale block receives Transaction fees, however, are not awarded to uncles.

It cannot be an ancestor of B An uncle must be a valid block header, but does not need to be a previously verified or even valid block An uncle must be different from all uncles included in previous blocks and all other uncles included in the same block non-double-inclusion For every uncle U in block B, the miner of B gets an additional 3. This limited version of GHOST, with uncles includable only up to 7 generations, was used for two reasons.

First, unlimited GHOST would include too many complications into the calculation of which uncles for a given block are valid. Second, unlimited GHOST with compensation as used in Ethereum removes the incentive for a miner to mine on the main chain and not the chain of a public attacker.

Fees Because every transaction published into the blockchain imposes on the network the cost of needing to download and verify it, there is a need for some regulatory mechanism, typically involving transaction fees, to prevent abuse. The default approach, used in Bitcoin, is to have purely voluntary fees, relying on miners to act as the gatekeepers and set dynamic minimums. This approach has been received very favorably in the Bitcoin community particularly because it is "market-based", allowing supply and demand between miners and transaction senders determine the price.

The problem with this line of reasoning is, however, that transaction processing is not a market; although it is intuitively attractive to construe transaction processing as a service that the miner is offering to the sender, in reality every transaction that a miner includes will need to be processed by every node in the network, so the vast majority of the cost of transaction processing is borne by third parties and not the miner that is making the decision of whether or not to include it.

Hence, tragedy-of-the-commons problems are very likely to occur. However, as it turns out this flaw in the market-based mechanism, when given a particular inaccurate simplifying assumption, magically cancels itself out. The argument is as follows. Suppose that: A transaction leads to k operations, offering the reward kR to any miner that includes it where R is set by the sender and k and R are roughly visible to the miner beforehand. An operation has a processing cost of C to any node ie.

A miner would be willing to process a transaction if the expected reward is greater than the cost. Note that R is the per-operation fee provided by the sender, and is thus a lower bound on the benefit that the sender derives from the transaction, and NC is the cost to the entire network together of processing an operation. Hence, miners have the incentive to include only those transactions for which the total utilitarian benefit exceeds the cost.

However, there are several important deviations from those assumptions in reality: The miner does pay a higher cost to process the transaction than the other verifying nodes, since the extra verification time delays block propagation and thus increases the chance the block will become a stale. There do exist nonmining full nodes. The mining power distribution may end up radically inegalitarian in practice. Speculators, political enemies and crazies whose utility function includes causing harm to the network do exist, and they can cleverly set up contracts where their cost is much lower than the cost paid by other verifying nodes.

Specifically: blk.

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